Inverse problems in stochastic computational dynamics

Computational Inverse Problems 3063 Workshop : Computational Inverse Problems

Inverse problem typically deal with the identification of unknown quantities from indirect measurements and appear in many areas in technology, medicine, biology, finance, and econometrics. The computational solution of such problems is a very active, interdisciplinary field with close connections to optimization, control theory, differential equations, asymptotic analysis, statistics, and prob...

A Computational Statistics Approach to Stochastic Inverse Problems and Uncertainty Quantification in Heat Transfer

As most engineering systems and processes operate in an uncertain environment, it becomes increasingly important to address their analysis and inverse design in a stochastic manner using statistical data-driven methods. Recent advances in computational Bayesian and spatial statistics enable complete and efficient solution procedures to such problems. Herein, a novel framework based on Bayesian ...

Nonlinear dynamics in mixed inverse problems

Computational and Variational Methods for Inverse Problems

Stochastic model reduction applied to inverse problems

This article describes the use of Gaussian Processes in model reduction techniques with application to inverse problems. Mainly, the work is focused on the proper construction of the model approximation, namely on training process based on minimal number of learning samples, by making use of automatic samples selection through computed standard deviation of model prediction. An example of appli...